code: def test_simple_runscript_sanity(tmpdir, task_name, model_type):
      RUN_NAME = f"{test_simple_runscript_sanity.__name__}_{task_name}_{model_type.replace('/','_')}"
      data_dir = str(tmpdir.mkdir("data"))
      exp_dir = str(tmpdir.mkdir("exp"))
  
      downloader.download_data([task_name], data_dir)
  
      args = run.RunConfiguration(
          run_name=RUN_NAME,
          exp_dir=exp_dir,
          data_dir=data_dir,
          hf_pretrained_model_name_or_path=model_type,
          tasks=task_name,
          train_examples_cap=16,
          train_batch_size=16,
          no_cuda=True,
      )
      run.run_simple(args)
  
      val_metrics = py_io.read_json(
          os.path.join(exp_dir, "runs", RUN_NAME, "val_metrics.json")
      )
      assert val_metrics["aggregated"] > 0
  
file_path: jiant/tests/proj/simple/test_runscript.py
imports: import os
  import pytest
  import torch
  import math
  import jiant.utils.python.io
  from jiant.proj.simple import runscript
  import jiant.scripts.download_data.runscript
  import jiant.utils.torch_utils
label_desc: Use image node_id 1 for calling a global function with example usage: test_simple_runscript_sanity(tmpdir, task_name, model_type) without return types